Hierarchical Graph Neural Network for Compressed Speech Steganalysis

Steganalysis methods based on deep learning DL often struggle with computational complexity and challenges in generalizing across different datasets. Incorporating a graph neural network GNN into steganalysis schemes enables the leveraging of relational data for improved detection accuracy and...

Hot-Swap MarkBoard: an Efficient Black-Box Watermarking Approach for Large-Scale Model Distribution

Recently, Deep Learning DL models have been increasingly deployed on end-user devices as On-Device AI, offering improved efficiency and privacy. However, this deployment trend poses more serious Intellectual Property IP risks, as models are distributed on numerous local devices, making them...

Flowable’s Summer 2025 Update Introduces Groundbreaking Agentic AI Capabilities

Flowable’s 2025.1 update brings powerful Agentic AI features to automate workflows, boost efficiency, and scale intelligent business operations...

SynthCTI: LLM-Driven Synthetic CTI Generation to Enhance MITRE Technique Mapping

Cyber Threat Intelligence CTI mining involves extracting structured insights from unstructured threat data, enabling organizations to understand and respond to evolving adversarial behavior. A key task in CTI mining is mapping threat descriptions to MITRE ATT&CK techniques. However, this process...

A Privacy-Centric Approach: Scalable and Secure Federated Learning Enabled by Hybrid Homomorphic Encryption

Federated Learning FL enables collaborative model training without sharing raw data, making it a promising approach for privacy-sensitive domains. Despite its potential, FL faces significant challenges, particularly in terms of communication overhead and data privacy. Privacy-preserving Technique...

Privacy-Preserving Drone Navigation through Homomorphic Encryption for Collision Avoidance

As drones increasingly deliver packages in neighborhoods, concerns about collisions arise. One solution is to share flight paths within a specific zip code, but this compromises business privacy by revealing delivery routes. For example, it could disclose which stores send packages to certain...

IDFace: Face Template Protection for Efficient and Secure Identification

As face recognition systems FRS become more widely used, user privacy becomes more important. A key privacy issue in FRS is protecting the user's face template, as the characteristics of the user's face image can be recovered from the template. Although recent advances in cryptographic tools such...

MAD-Spear: a Conformity-Driven Prompt Injection Attack on Multi-Agent Debate Systems

Multi-agent debate MAD systems leverage collaborative interactions among large language models LLMs agents to improve reasoning capabilities. While recent studies have focused on increasing the accuracy and scalability of MAD systems, their security vulnerabilities have received limited attention...

Improving IT efficiency with Microsoft Security Copilot in Microsoft Intune and Microsoft Entra

When Microsoft introduced Microsoft Security Copilot last year, our vision was to empower organizations with generative AI that helps security and IT teams simplify operations and respond faster. Since then, we’ve continuously innovated and learned alongside our customers. They consistently tell ...

BandFuzz: an ML-Powered Collaborative Fuzzing Framework

Collaborative fuzzing has recently emerged as a technique that combines multiple individual fuzzers and dynamically chooses the appropriate combinations suited for different programs. Unlike individual fuzzers, which rely on specific assumptions to maintain their effectiveness, collaborative...

Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models

Automated Program Repair APR is essential for ensuring software reliability and quality while enhancing efficiency and reducing developers' workload. Although rule-based and learning-based APR methods have demonstrated their effectiveness, their performance was constrained by the defect type of...

Implementing and Evaluating Post-Quantum DNSSEC in CoreDNS

The emergence of quantum computers poses a significant threat to current secure service, application and/or protocol implementations that rely on RSA and ECDSA algorithms, for instance DNSSEC, because public-key cryptography based on number factorization or discrete logarithm is vulnerable to...

CLIProv: a Contrastive Log-To-Intelligence Multimodal Approach for Threat Detection and Provenance Analysis

With the increasing complexity of cyberattacks, the proactive and forward-looking nature of threat intelligence has become more crucial for threat detection and provenance analysis. However, translating high-level attack patterns described in Tactics, Techniques, and Procedures TTP intelligence...

SUSE CVE-2025-38297

In the Linux kernel, the following vulnerability has been resolved: PM: EM: Fix potential division-by-zero error in emcomputecosts When the device is of a non-CPU type, tablei.performance won't be initialized in the previous eminitperformance, resulting in division by zero when calculating costs ...

DEBIAN-CVE-2025-38297

In the Linux kernel, the following vulnerability has been resolved: PM: EM: Fix potential division-by-zero error in emcomputecosts When the device is of a non-CPU type, tablei.performance won't be initialized in the previous eminitperformance, resulting in division by zero when calculating costs ...

UBUNTU-CVE-2025-38272

In the Linux kernel, the following vulnerability has been resolved: net: dsa: b53: do not enable EEE on bcm63xx BCM63xx internal switches do not support EEE, but provide multiple RGMII ports where external PHYs may be connected. If one of these PHYs are EEE capable, we may try to enable EEE for t...

UBUNTU-CVE-2025-38297

In the Linux kernel, the following vulnerability has been resolved: PM: EM: Fix potential division-by-zero error in emcomputecosts When the device is of a non-CPU type, tablei.performance won't be initialized in the previous eminitperformance, resulting in division by zero when calculating costs ...

CVE-2025-38297 PM: EM: Fix potential division-by-zero error in em_compute_costs()

In the Linux kernel, the following vulnerability has been resolved: PM: EM: Fix potential division-by-zero error in emcomputecosts When the device is of a non-CPU type, tablei.performance won't be initialized in the previous eminitperformance, resulting in division by zero when calculating costs ...

CVE-2025-38297

CVE-2025-38297: In the Linux kernel, a division-by-zero could occur in em_compute_costs() for non-CPU devices due to uninitialized table[i].performance. The fix adds a _is_cpu_device(dev) check to em_init_performance() paths to prevent the division. Public advisories (e.g., openSUSE SUSE-SU-2026:...

CVE-2025-38297 PM: EM: Fix potential division-by-zero error in em_compute_costs()

In the Linux kernel, the following vulnerability has been resolved: PM: EM: Fix potential division-by-zero error in emcomputecosts When the device is of a non-CPU type, tablei.performance won't be initialized in the previous eminitperformance, resulting in division by zero when calculating costs ...